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swift-mirror/stdlib/public/SDK/simd/simd.swift.gyb

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Swift

//===----------------------------------------------------------*- swift -*-===//
//
// This source file is part of the Swift.org open source project
//
// Copyright (c) 2014 - 2016 Apple Inc. and the Swift project authors
// Licensed under Apache License v2.0 with Runtime Library Exception
//
// See http://swift.org/LICENSE.txt for license information
// See http://swift.org/CONTRIBUTORS.txt for the list of Swift project authors
//
//===----------------------------------------------------------------------===//
// simd.h overlays for Swift
//===----------------------------------------------------------------------===//
import Swift
import Darwin
@_exported import simd
% component = ['x','y','z','w']
% scalar_types = ['Float','Double','Int32']
% ctype = { 'Float':'float', 'Double':'double', 'Int32':'int' }
% llvm_type = { 'Float':'FPIEEE32', 'Double':'FPIEEE64', 'Int32':'Int32' }
% floating_types = ['Float','Double']
% cardinal = { 2:'two', 3:'three', 4:'four'}
% hash_scales = ['1', '3', '5', '11']
% one_minus_ulp = { 'Float':'0x1.fffffep-1', 'Double':'0x1.fffffffffffffp-1' }
% for type in scalar_types:
% for size in [2, 3, 4]:
// Workaround <rdar://problem/18900352>
% vectype = ctype[type] + str(size)
% llvm_vectype = "Vec" + str(size) + "x" + llvm_type[type]
% vecsize = (8 if type == 'Double' else 4) * (2 if size == 2 else 4)
% extractelement = "extractelement_" + llvm_vectype + "_Int32"
% insertelement = "insertelement_" + llvm_vectype + "_" + llvm_type[type] + "_Int32"
% is_floating = type in floating_types
% wrap = "" if is_floating else "&"
/// A vector of ${cardinal[size]} `${type}`. This corresponds to the C and
/// Obj-C type `vector_${vectype}` and the C++ type `simd::${vectype}`.
@_alignment(${vecsize})
public struct ${vectype} :
ArrayLiteralConvertible, CustomDebugStringConvertible {
public var _vector: Builtin.${llvm_vectype}
% for i in xrange(size):
public var ${component[i]} : ${type} {
@_transparent
get {
let elt = Builtin.${extractelement}(_vector,
(${i} as Int32)._value)
return ${type}(_bits: elt)
}
@_transparent
set {
_vector = Builtin.${insertelement}(_vector,
newValue._value,
(${i} as Int32)._value)
}
}
% end
/// Initialize to the zero vector.
@_transparent
public init() { self.init(0) }
@_transparent
public init(_bits: Builtin.${llvm_vectype}) {
_vector = _bits
}
/// Initialize a vector with the specified elements.
@_transparent
public init(${', '.join(map(lambda c: '_ ' + c + ': ' + type, component[:size]))}) {
var v: Builtin.${llvm_vectype} = Builtin.zeroInitializer()
% for i in xrange(size):
v = Builtin.${insertelement}(v,
${component[i]}._value,
(${i} as Int32)._value)
% end
_vector = v
}
/// Initialize a vector with the specified elements.
@_transparent
public init(${', '.join(map(lambda c: c + ': ' + type, component[:size]))}) {
self.init(${', '.join(c for c in component[:size])})
}
/// Initialize to a vector with all elements equal to `scalar`.
@_transparent
public init(_ scalar: ${type}) {
self.init(${', '.join(['scalar']*size)})
}
/// Initialize to a vector with elements taken from `array`.
///
/// - Precondition: `array` must have exactly ${cardinal[size]} elements.
public init(_ array: [${type}]) {
_precondition(array.count == ${size},
"${vectype} requires a ${cardinal[size]}-element array")
self.init(${', '.join(map(lambda i:
'array[' + str(i) + ']',
range(size)))})
}
/// Initialize using `arrayLiteral`.
///
/// - Precondition: the array literal must exactly ${cardinal[size]} elements.
public init(arrayLiteral elements: ${type}...) { self.init(elements) }
/// Access individual elements of the vector via subscript.
public subscript(index: Int) -> ${type} {
@_transparent
get {
_precondition(index >= 0, "vector index out of range")
_precondition(index < ${size}, "vector index out of range")
let elt = Builtin.${extractelement}(_vector,
Int32(index)._value)
return ${type}(_bits: elt)
}
@_transparent
set(value) {
_precondition(index >= 0, "vector index out of range")
_precondition(index < ${size}, "vector index out of range")
_vector = Builtin.${insertelement}(_vector,
value._value,
Int32(index)._value)
}
}
/// Debug string representation
public var debugDescription: String {
return "${vectype}(${', '.join(map(lambda c:
'\\(' + c + ')',
component[:size]))})"
}
/// Helper for matrix debug representations
internal var _descriptionAsArray: String {
get {
return "[${', '.join(map(lambda c:
'\\(' + c + ')',
component[:size]))}]"
}
}
}
/// Vector sum of `lhs` and `rhs`.
@inline(__always)
@warn_unused_result
public func ${wrap}+(lhs: ${vectype}, rhs: ${vectype}) -> ${vectype} {
return ${vectype}(_bits:
%if is_floating:
Builtin.fadd_${llvm_vectype}(
%else:
Builtin.add_${llvm_vectype}(
%end
lhs._vector, rhs._vector))
}
/// Vector difference of `lhs` and `rhs`.
@inline(__always)
@warn_unused_result
public func ${wrap}-(lhs: ${vectype}, rhs: ${vectype}) -> ${vectype} {
return ${vectype}(_bits:
%if is_floating:
Builtin.fsub_${llvm_vectype}(
%else:
Builtin.sub_${llvm_vectype}(
%end
lhs._vector, rhs._vector))
}
/// Negation of `rhs`.
@inline(__always)
@warn_unused_result
public prefix func -(rhs: ${vectype}) -> ${vectype} {
return ${vectype}(0) ${wrap}- rhs
}
/// Elementwise product of `lhs` and `rhs`. A.k.a. the Hadamard or Schur
/// product of the two vectors.
@inline(__always)
@warn_unused_result
public func ${wrap}*(lhs: ${vectype}, rhs: ${vectype}) -> ${vectype} {
return ${vectype}(_bits:
%if is_floating:
Builtin.fmul_${llvm_vectype}(
%else:
Builtin.mul_${llvm_vectype}(
%end
lhs._vector, rhs._vector))
}
/// Elementwise quotient of `lhs` and `rhs`. This is the inverse operation
/// of the elementwise product.
@inline(__always)
@warn_unused_result
public func /(lhs: ${vectype}, rhs: ${vectype}) -> ${vectype} {
return ${vectype}(_bits:
%if is_floating:
Builtin.fdiv_${llvm_vectype}(
%else:
Builtin.sdiv_${llvm_vectype}(
%end
lhs._vector, rhs._vector))
}
/// Add `rhs` to `lhs`.
% if is_floating:
@inline(__always)
public func +=(lhs: inout ${vectype}, rhs: ${vectype}) -> Void {
lhs = lhs + rhs
}
/// Subtract `rhs` from `lhs`.
@inline(__always)
public func -=(lhs: inout ${vectype}, rhs: ${vectype}) -> Void {
lhs = lhs - rhs
}
/// Multiply `lhs` by `rhs` (elementwise).
@inline(__always)
public func *=(lhs: inout ${vectype}, rhs: ${vectype}) -> Void {
lhs = lhs * rhs
}
% end
/// Divide `lhs` by `rhs` (elementwise).
@inline(__always)
public func /=(lhs: inout ${vectype}, rhs: ${vectype}) -> Void {
lhs = lhs / rhs
}
/// Scalar-Vector product.
@inline(__always)
@warn_unused_result
public func ${wrap}*(lhs: ${type}, rhs: ${vectype}) -> ${vectype} {
return ${vectype}(lhs) ${wrap}* rhs
}
/// Scalar-Vector product.
@inline(__always)
@warn_unused_result
public func ${wrap}*(lhs: ${vectype}, rhs: ${type}) -> ${vectype} {
return lhs ${wrap}* ${vectype}(rhs)
}
% if is_floating:
/// Scales `lhs` by `rhs`.
@inline(__always)
public func *=(lhs: inout ${vectype}, rhs: ${type}) -> Void {
lhs = lhs * rhs
}
% end
/// Elementwise absolute value of a vector. The result is a vector of the same
/// length with all elements positive.
@inline(__always)
@warn_unused_result
public func abs(x: ${vectype}) -> ${vectype} {
return ${vectype}(${', '.join(map(lambda c: \
'abs(x.' + c + ')', \
component[:size]))})
}
/// Elementwise minimum of two vectors. Each component of the result is the
/// smaller of the corresponding component of the inputs.
@inline(__always)
@warn_unused_result
public func min(x: ${vectype}, _ y: ${vectype}) -> ${vectype} {
return ${vectype}(${', '.join(map(lambda c: \
'min(x.' + c + ',y.' + c + ')', \
component[:size]))})
}
/// Elementwise maximum of two vectors. Each component of the result is the
/// larger of the corresponding component of the inputs.
@inline(__always)
@warn_unused_result
public func max(x: ${vectype}, _ y: ${vectype}) -> ${vectype} {
return ${vectype}(${', '.join(map(lambda c: \
'max(x.' + c + ',y.' + c + ')', \
component[:size]))})
}
/// Vector-scalar minimum. Each component of the result is the minimum of the
/// corresponding element of the input vector and the scalar.
@inline(__always)
@warn_unused_result
public func min(vector: ${vectype}, _ scalar: ${type}) -> ${vectype} {
return min(vector, ${vectype}(scalar))
}
/// Vector-scalar maximum. Each component of the result is the maximum of the
/// corresponding element of the input vector and the scalar.
@inline(__always)
@warn_unused_result
public func max(vector: ${vectype}, _ scalar: ${type}) -> ${vectype} {
return max(vector, ${vectype}(scalar))
}
/// Each component of the result is the corresponding element of `x` clamped to
/// the range formed by the corresponding elements of `min` and `max`. Any
/// lanes of `x` that contain NaN will end up with the `min` value.
@inline(__always)
@warn_unused_result
public func clamp(x: ${vectype},
min: ${vectype},
max: ${vectype})
-> ${vectype} {
return simd.min(simd.max(x, min), max)
}
/// Clamp each element of `x` to the range [`min`, max]. If any lane of `x` is
/// NaN, the corresponding lane of the result is `min`.
@inline(__always)
@warn_unused_result
public func clamp(x: ${vectype},
min: ${type},
max: ${type})
-> ${vectype} {
return simd.min(simd.max(x, min), max)
}
/// Sum of the elements of the vector.
@inline(__always)
@warn_unused_result
public func reduce_add(x: ${vectype}) -> ${type} {
return ${(' '+wrap+'+ ').join(map(lambda x:'x.'+x, component[:size]))}
}
/// Minimum element of the vector.
@inline(__always)
@warn_unused_result
public func reduce_min(x: ${vectype}) -> ${type} {
return min(${', '.join(map(lambda x:'x.'+x, component[:size]))})
}
/// Maximum element of the vector.
@inline(__always)
@warn_unused_result
public func reduce_max(x: ${vectype}) -> ${type} {
return max(${', '.join(map(lambda x:'x.'+x, component[:size]))})
}
% if is_floating:
/// Sign of a vector. Each lane contains -1 if the corresponding lane of `x`
/// is less than zero, +1 if the corresponding lane of `x` is greater than
/// zero, and 0 otherwise.
@inline(__always)
@warn_unused_result
public func sign(x: ${vectype}) -> ${vectype} {
return ${vectype}(${', '.join(map(lambda c: \
'sign(x.' + c + ')', \
component[:size]))})
}
/// Linear interpolation between `x` (at `t=0`) and `y` (at `t=1`). May be
/// used with `t` outside of [0, 1] as well.
@inline(__always)
@warn_unused_result
public func mix(x: ${vectype}, _ y: ${vectype}, t: ${vectype}) -> ${vectype} {
return x + t*(y-x)
}
/// Linear interpolation between `x` (at `t=0`) and `y` (at `t=1`). May be
/// used with `t` outside of [0, 1] as well.
@inline(__always)
@warn_unused_result
public func mix(x: ${vectype}, _ y: ${vectype}, t: ${type}) -> ${vectype} {
return x + t*(y-x)
}
/// Elementwise reciprocal.
@inline(__always)
@warn_unused_result
public func recip(x: ${vectype}) -> ${vectype} {
return ${vectype}(${', '.join(map(lambda c: \
'recip(x.' + c + ')', \
component[:size]))})
}
/// Elementwise reciprocal square root.
@inline(__always)
@warn_unused_result
public func rsqrt(x: ${vectype}) -> ${vectype} {
return ${vectype}(${', '.join(map(lambda c: \
'rsqrt(x.' + c + ')', \
component[:size]))})
}
/// Alternate name for minimum of two floating-point vectors.
@inline(__always)
@warn_unused_result
public func fmin(x: ${vectype}, _ y: ${vectype}) -> ${vectype} {
return min(x, y)
}
/// Alternate name for maximum of two floating-point vectors.
@inline(__always)
@warn_unused_result
public func fmax(x: ${vectype}, _ y: ${vectype}) -> ${vectype} {
return max(x, y)
}
/// Each element of the result is the smallest integral value greater than or
/// equal to the corresponding element of the input.
@inline(__always)
@warn_unused_result
public func ceil(x: ${vectype}) -> ${vectype} {
return ${vectype}(${', '.join(map(lambda c: \
'ceil(x.' + c + ')', \
component[:size]))})
}
/// Each element of the result is the largest integral value less than or equal
/// to the corresponding element of the input.
@inline(__always)
@warn_unused_result
public func floor(x: ${vectype}) -> ${vectype} {
return ${vectype}(${', '.join(map(lambda c: \
'floor(x.' + c + ')', \
component[:size]))})
}
/// Each element of the result is the closest integral value with magnitude
/// less than or equal to that of the corresponding element of the input.
@inline(__always)
@warn_unused_result
public func trunc(x: ${vectype}) -> ${vectype} {
return ${vectype}(${', '.join(map(lambda c: \
'trunc(x.' + c + ')', \
component[:size]))})
}
/// `x - floor(x)`, clamped to lie in the range [0,1). Without this clamp step,
/// the result would be 1.0 when `x` is a very small negative number, which may
/// result in out-of-bounds table accesses in common usage.
@inline(__always)
@warn_unused_result
public func fract(x: ${vectype}) -> ${vectype} {
return fmin(x - floor(x), ${vectype}(${one_minus_ulp[type]}))
}
/// 0.0 if `x < edge`, and 1.0 otherwise.
@inline(__always)
@warn_unused_result
public func step(x: ${vectype}, edge: ${vectype}) -> ${vectype} {
return ${vectype}(${', '.join(map(lambda c: \
'step(x.' + c + ', edge: edge.' + c + ')', \
component[:size]))})
}
/// 0.0 if `x < edge0`, 1.0 if `x > edge1`, and cubic interpolation between
/// 0 and 1 in the interval [edge0, edge1].
@inline(__always)
@warn_unused_result
public func smoothstep(x: ${vectype},
edge0: ${vectype},
edge1: ${vectype})
-> ${vectype} {
let t = clamp((x-edge0)/(edge1-edge0), min: 0, max: 1)
return t*t*(${vectype}(3) - 2*t)
}
/// Dot product of `x` and `y`.
@inline(__always)
@warn_unused_result
public func dot(x: ${vectype}, _ y: ${vectype}) -> ${type} {
return reduce_add(x*y)
}
/// Projection of `x` onto `y`.
@inline(__always)
@warn_unused_result
public func project(x: ${vectype}, _ y: ${vectype}) -> ${vectype} {
return dot(x,y)/dot(y,y)*y
}
/// Length of `x`, squared. This is more efficient to compute than the length,
/// so you should use it if you only need to compare lengths to each other.
/// I.e. instead of writing:
///
/// if (length(x) < length(y)) { ... }
///
/// use:
///
/// if (length_squared(x) < length_squared(y)) { ... }
///
/// Doing it this way avoids one or two square roots, which is a fairly costly
/// operation.
@inline(__always)
@warn_unused_result
public func length_squared(x: ${vectype}) -> ${type} {
return dot(x,x)
}
/// Length (two-norm or "Euclidean norm") of `x`.
@inline(__always)
@warn_unused_result
public func length(x: ${vectype}) -> ${type} {
return sqrt(length_squared(x))
}
/// The one-norm (or "taxicab norm") of `x`.
@inline(__always)
@warn_unused_result
public func norm_one(x: ${vectype}) -> ${type} {
return reduce_add(abs(x))
}
/// The infinity-norm (or "sup norm") of `x`.
@inline(__always)
@warn_unused_result
public func norm_inf(x: ${vectype}) -> ${type} {
return reduce_max(abs(x))
}
/// Distance between `x` and `y`, squared.
@inline(__always)
@warn_unused_result
public func distance_squared(x: ${vectype}, _ y: ${vectype}) -> ${type} {
return length_squared(x - y)
}
/// Distance between `x` and `y`.
@inline(__always)
@warn_unused_result
public func distance(x: ${vectype}, _ y: ${vectype}) -> ${type} {
return length(x - y)
}
/// Unit vector pointing in the same direction as `x`.
@inline(__always)
@warn_unused_result
public func normalize(x: ${vectype}) -> ${vectype} {
return x * rsqrt(length_squared(x))
}
/// `x` reflected through the hyperplane with unit normal vector `n`, passing
/// through the origin. E.g. if `x` is [1,2,3] and `n` is [0,0,1], the result
/// is [1,2,-3].
@inline(__always)
@warn_unused_result
public func reflect(x: ${vectype}, n: ${vectype}) -> ${vectype} {
return x - 2*dot(x,n)*n
}
/// The refraction direction given unit incident vector `x`, unit surface
/// normal `n`, and index of refraction `eta`. If the angle between the
/// incident vector and the surface is so small that total internal reflection
/// occurs, zero is returned.
@inline(__always)
@warn_unused_result
public func refract(x: ${vectype},
n: ${vectype},
eta: ${type})
-> ${vectype} {
let k = 1 - eta*eta*(1 - dot(x,n)*dot(x,n))
if k >= 0 { return eta*x - (eta*dot(x,n) + sqrt(k))*n }
return ${vectype}(0)
}
% end # if is_floating
% end # for size in [2, 3, 4]
% if is_floating:
// Scalar versions of common operations:
/// Returns -1 if `x < 0`, +1 if `x > 0`, and 0 otherwise (`sign(NaN)` is 0).
@inline(__always)
@warn_unused_result
public func sign(x: ${type}) -> ${type} {
return x < 0 ? -1 : (x > 0 ? 1 : 0)
}
/// Reciprocal.
@inline(__always)
@warn_unused_result
public func recip(x: ${type}) -> ${type} { return 1/x }
/// Reciprocal square root.
@inline(__always)
@warn_unused_result
public func rsqrt(x: ${type}) -> ${type} { return 1/sqrt(x) }
/// Returns 0.0 if `x < edge`, and 1.0 otherwise.
@inline(__always)
@warn_unused_result
public func step(x: ${type}, edge: ${type}) -> ${type} {
return x < edge ? 0.0 : 1.0
}
/// Interprets two two-dimensional vectors as three-dimensional vectors in the
/// xy-plane and computes their cross product, which lies along the z-axis.
@inline(__always)
@warn_unused_result
public func cross(x: ${ctype[type]}2,
_ y: ${ctype[type]}2)
-> ${ctype[type]}3 {
return ${ctype[type]}3(0, 0, x.x*y.y - x.y*y.x)
}
/// Cross-product of two three-dimensional vectors. The resulting vector is
/// perpendicular to the plane determined by `x` and `y`, with length equal to
/// the oriented area of the parallelogram they determine.
@inline(__always)
@warn_unused_result
public func cross(x: ${ctype[type]}3,
_ y: ${ctype[type]}3)
-> ${ctype[type]}3 {
return ${ctype[type]}3(x.y*y.z - x.z*y.y, x.z*y.x - x.x*y.z, x.x*y.y - x.y*y.x)
}
% else: # !is_floating
// Integer vector types only support wrapping arithmetic. Make the non-wrapping
// operators unavailable so that fixits guide users to the unchecked operations.
@available(*, unavailable, renamed="&+",
message="integer vector types do not support checked arithmetic; use the wrapping operations instead")
public func +(x: ${vectype}, y: ${vectype}) -> ${vectype} {
fatalError("unavailable function cannot be called")
}
@available(*, unavailable, renamed="&-",
message="integer vector types do not support checked arithmetic; use the wrapping operations instead")
public func -(x: ${vectype}, y: ${vectype}) -> ${vectype} {
fatalError("unavailable function cannot be called")
}
@available(*, unavailable, renamed="&*",
message="integer vector types do not support checked arithmetic; use the wrapping operations instead")
public func *(x: ${vectype}, y: ${vectype}) -> ${vectype} {
fatalError("unavailable function cannot be called")
}
@available(*, unavailable, renamed="&*",
message="integer vector types do not support checked arithmetic; use the wrapping operations instead")
public func *(x: ${vectype}, y: ${type}) -> ${vectype} {
fatalError("unavailable function cannot be called")
}
@available(*, unavailable, renamed="&*",
message="integer vector types do not support checked arithmetic; use the wrapping operations instead")
public func *(x: ${type}, y: ${vectype}) -> ${vectype} {
fatalError("unavailable function cannot be called")
}
@available(*, unavailable,
message="integer vector types do not support checked arithmetic; use the wrapping operation 'x = x &+ y' instead")
public func +=(x: inout ${vectype}, y: ${vectype}) {
fatalError("unavailable function cannot be called")
}
@available(*, unavailable,
message="integer vector types do not support checked arithmetic; use the wrapping operation 'x = x &- y' instead")
public func -=(x: inout ${vectype}, y: ${vectype}) {
fatalError("unavailable function cannot be called")
}
@available(*, unavailable,
message="integer vector types do not support checked arithmetic; use the wrapping operation 'x = x &* y' instead")
public func *=(x: inout ${vectype}, y: ${vectype}) {
fatalError("unavailable function cannot be called")
}
@available(*, unavailable,
message="integer vector types do not support checked arithmetic; use the wrapping operation 'x = x &* y' instead")
public func *=(x: inout ${vectype}, y: ${type}) {
fatalError("unavailable function cannot be called")
}
% end # is_floating
% end # for type in scalar_types
% for type in floating_types:
% for rows in [2,3,4]:
// Workaround <rdar://problem/18900352>
% for cols in [2,3,4]:
// Workaround <rdar://problem/18900352>
% mattype = ctype[type] + str(cols) + 'x' + str(rows)
% diagsize = rows if rows < cols else cols
% coltype = ctype[type] + str(rows)
% rowtype = ctype[type] + str(cols)
% diagtype = ctype[type] + str(diagsize)
% transtype = ctype[type] + str(rows) + 'x' + str(cols)
% cmatrix = 'matrix_' + mattype
public struct ${mattype} : CustomDebugStringConvertible {
internal var _columns: (${', '.join([coltype]*cols)})
/// Initialize matrix to zero.
public init() {
% for i in range(cols):
_columns.${i} = ${coltype}()
% end
}
/// Initialize matrix to have `scalar` on main diagonal, zeros elsewhere.
public init(_ scalar: ${type}) {
self.init(diagonal: ${diagtype}(scalar))
}
/// Initialize matrix to have specified `diagonal`, and zeros elsewhere.
public init(diagonal: ${diagtype}) {
% for i in range(cols):
self._columns.${i} = ${coltype}()
% end
% for i in range(diagsize):
self._columns.${i}.${component[i]} = diagonal.${component[i]}
% end
}
/// Initialize matrix to have specified `columns`.
public init(_ columns: [${coltype}]) {
_precondition(columns.count == ${cols}, "Requires array of ${cols} vectors")
% for i in range(cols):
self._columns.${i} = columns[${i}]
% end
}
/// Initialize matrix to have specified `rows`.
public init(rows: [${rowtype}]) {
_precondition(rows.count == ${rows}, "Requires array of ${rows} vectors")
% for i in range(cols):
self._columns.${i} = [${', '.join(map(lambda j:
'rows[' + str(j) + '].' + component[i],
range(rows)))}]
% end
}
/// Initialize matrix to have specified `columns`.
internal init(${', '.join(map(lambda i:
'_ col' + str(i) + ': ' + coltype,
range(cols)))}) {
% for i in range(cols):
self._columns.${i} = col${i}
% end
}
/// Initialize matrix from corresponding C matrix type.
public init(_ cmatrix: ${cmatrix}) {
self = unsafeBitCast(cmatrix, to: ${mattype}.self)
}
/// Get the matrix as the corresponding C matrix type.
public var cmatrix: ${cmatrix} {
get { return unsafeBitCast(self, to: ${cmatrix}.self) }
}
/// Access to individual columns.
public subscript(column: Int) -> ${coltype} {
get {
switch(column) {
% for i in range(cols):
case ${i}: return _columns.${i}
% end
default: _preconditionFailure("Column index out of range")
}
}
set (value) {
switch(column) {
% for i in range(cols):
case ${i}: _columns.${i} = value
% end
default: _preconditionFailure("Column index out of range")
}
}
}
/// Access to individual elements.
public subscript(column: Int, row: Int) -> ${type} {
get { return self[column][row] }
set (value) { self[column][row] = value }
}
public var debugDescription: String {
return "${mattype}([${', '.join(map(lambda i: \
'\(_columns.' + str(i) + '._descriptionAsArray)',
range(cols)))}])"
}
/// Transpose of the matrix.
public var transpose: ${transtype} {
get {
return ${transtype}([
% for i in range(rows):
[${', '.join(map(lambda j: \
'self[' + str(j) + ',' + str(i) + ']', \
range(cols)))}],
% end # for i in range(rows)
])
}
}
% if rows == cols:
/// Inverse of the matrix if it exists, otherwise the contents of the
/// resulting matrix are undefined.
public var inverse: ${mattype} {
get {
% inverse_func = '__invert_' + ('f' if type == 'Float' else 'd') + str(cols)
return ${mattype}(${inverse_func}(self.cmatrix))
}
}
% end
}
/// Sum of two matrices.
@warn_unused_result
public func +(lhs: ${mattype}, rhs: ${mattype}) -> ${mattype} {
return ${mattype}(${', '.join(map(lambda i: \
'lhs._columns.'+str(i)+' + rhs._columns.'+str(i), \
range(cols)))})
}
/// Negation of a matrix.
@warn_unused_result
public prefix func -(rhs: ${mattype}) -> ${mattype} {
return ${mattype}(${', '.join(map(lambda i: \
'-rhs._columns.'+str(i), \
range(cols)))})
}
/// Difference of two matrices.
@warn_unused_result
public func -(lhs: ${mattype}, rhs: ${mattype}) -> ${mattype} {
return ${mattype}(${', '.join(map(lambda i: \
'lhs._columns.'+str(i)+' - rhs._columns.'+str(i), \
range(cols)))})
}
public func +=(lhs: inout ${mattype}, rhs: ${mattype}) -> Void {
lhs = lhs + rhs
}
public func -=(lhs: inout ${mattype}, rhs: ${mattype}) -> Void {
lhs = lhs - rhs;
}
/// Scalar-Matrix multiplication.
@warn_unused_result
public func *(lhs: ${type}, rhs: ${mattype}) -> ${mattype} {
return ${mattype}(${', '.join(map(lambda i: \
'lhs*rhs._columns.'+str(i), \
range(cols)))})
}
/// Matrix-Scalar multiplication.
@warn_unused_result
public func *(lhs: ${mattype}, rhs: ${type}) -> ${mattype} {
return rhs*lhs
}
public func *=(lhs: inout ${mattype}, rhs: ${type}) -> Void {
lhs = lhs*rhs
}
/// Matrix-Vector multiplication. Keep in mind that matrix types are named
/// `${type}NxM` where `N` is the number of *columns* and `M` is the number of
/// *rows*, so we multiply a `${type}3x2 * ${type}3` to get a `${type}2`, for
/// example.
@warn_unused_result
public func *(lhs: ${mattype}, rhs: ${rowtype}) -> ${coltype} {
return ${' + '.join(map(lambda i: \
'lhs._columns.'+str(i)+'*rhs.'+component[i], \
range(cols)))}
}
/// Vector-Matrix multiplication.
@warn_unused_result
public func *(lhs: ${coltype}, rhs: ${mattype}) -> ${rowtype} {
return ${rowtype}(${', '.join(map(lambda i: \
'dot(lhs, rhs._columns.'+str(i)+')', \
range(cols)))})
}
% for k in [2,3,4]:
/// Matrix multiplication (the "usual" matrix product, not the elementwise
/// product).
% lhstype = ctype[type] + str(k) + 'x' + str(rows)
% rhstype = ctype[type] + str(cols) + 'x' + str(k)
@warn_unused_result
public func *(lhs: ${lhstype}, rhs: ${rhstype}) -> ${mattype} {
return ${mattype}(${', '.join(map(lambda i: \
'lhs*rhs._columns.'+str(i), \
range(cols)))})
}
% end # for k in [2,3,4]
% rhstype = ctype[type] + str(cols) + 'x' + str(cols)
/// Matrix multiplication (the "usual" matrix product, not the elementwise
/// product).
public func *=(lhs: inout ${mattype}, rhs: ${rhstype}) -> Void {
lhs = lhs*rhs
}
% end # for cols in [2,3,4]
% end # for rows in [2,3,4]
% end # for type in floating_types